Understand the Potential of your Data with Data Discovery
- April 29, 2023
Imagine trying to find five needles in a haystack. Now, imagine trying to find those same five needles using a metal detector – one equipped with multi-scan and multi-frequency capabilities designed for identifying and locating the items for which you’re looking. How long would each task take? How easy (or difficult) would they be?
Data discovery is defined as a process of identifying and exploring large volumes of data to understand its potential value for analysis. It is a crucial process that involves identifying and locating relevant data assets within an organization. With the exponential growth of data in the enterprise, data discovery has become an essential component of data management that helps with making business decisions.
Today, data consumers spend far too much time seeking, accessing, preparing and manually cataloging data. This delays the uncovering of analytics insights necessary to drive quantifiable business value. Many organizations are facing several of the same issues.
First, there’s the data silos problem, which is when data is stored in various systems within an organization, making it difficult to discover all relevant data assets. Next, there’s a lack of standardization. Since data is often stored in different formats, it’s difficult to standardize and integrate from multiple data systems. There’s also the reality that the volume of data generated by organizations is increasing rapidly, making it challenging to identify and manage data assets. Organizations also struggle with data quality, when the quality of data varies across the data systems and makes it difficult to ensure that data’s accuracy and reliability. Finally, there’s the data access problem. As data reside in different systems, it’s a challenging task for admins to make sure the right users have access to critical data assets.
So, how do we address data silos, lack of standardization, data volume, data quality and access challenges?
Enterprises can organize and standardize large volumes of data by enabling data discovery across different data systems. First, data discovery enables organizations to identify and locate valuable data assets that were previously unknown or underutilized. Data discovery also helps identify data quality issues such as duplicates and inconsistencies and takes required actions to improve the quality of data.
Organizations can use data discovery to find and analyze data quickly and make informed business decisions faster. Data discovery also helps users identify data sources that can be integrated to provide a more comprehensive view of their data, which also enables them to implement access control over data assets. Best of all, data discovery establishes a clear line of sight from data to value creation, which is the ultimate goal of data management.
The best approach to kicking off your data discovery process involves a few steps.
Data discovery is an essential process that can help organizations unlock the potential of their data assets by creating a clear line of sight from data to value creation. Enterprises can leverage data discovery to improve quality of their data and support data consumption efficiently. It enhances the quality of results and enables decision-making as an effective process for business users.
Learn more about the Data Management Journey with our interactive infographic here. And stay on the lookout for our blog on step three of the data management journey, coming next month. You can also learn more about Dell Data Management solutions on our Enterprise Data Management page.
Introduction: The Dell Data Management Journey Map